Simulation and Optimization

1. Front Matter

   Pages I-X

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2. Optimization of Simulated Systems

   1. Performance evaluation for the score function method in sensitivity analysis and stochastic optimization

      • Søren Asmussen, Reuven Rubinstein

      Pages 1-13

   2. Experimental Results for Gradient Estimation and Optimization of a Markov Chain in Steady-State

      • Pierre L’Ecuyer, Nataly Giroux, Peter W. Glynn

      Pages 14-23

   3. Optimization of Stochastic Discrete Event Dynamic Systems: A Survey of Some Recent Results

      • Alexei A. Gaivoronski

      Pages 24-44

   4. Sensitivity Analysis of Simulation Experiments: Regression Analysis and Statistical Design

      • Jack P. C. Kleijnen

      Pages 45-54

3. Optimization and Stochastic Optimization

   1. A Stochastic Optimization Approach for Training the Parameters in Neural Networks

      • Norio Baba

      Pages 55-79

   2. Integrated stochastic approximation program system

      • Pavel Charamza

      Pages 80-100

   3. Lexicographic Duality in Linear Optimization

      • I. I. Eremin

      Pages 101-108

   4. Dual Optimization of Dynamic Systems

      • R. Gabasov, F. Kirillova

      Pages 109-118

   5. Stochastic Approximation Via Averaging: The Polyak’s Approach Revisited

      • G. Yin

      Pages 119-134

4. Random Numbers

   1. Nonuniform Random Numbers: A Sensitivity Analysis for Transformation Methods

      • Lothar Afflerbach, Wolfgang Hörmann

      Pages 135-144

   2. Nonlinear Methods for Pseudorandom Number and Vector Generation

      • Harald Niederreiter

      Pages 145-153

   3. Sampling from Discrete and Continuous Distributions with C-Rand

      • Ernst Stadlober, Ralf Kremer

      Pages 154-162

5. Back Matter

   Pages 163-166

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This volume contains selected papers presented at the "International Workshop on Computationally Intensive Methods in Simulation and Op­ th th timization" held from 23 to 25 August 1990 at the International Institute for Applied Systems Analysis (nASA) in La~enburg, Austria. The purpose of this workshop was to evaluate and to compare recently developed methods dealing with optimization in uncertain environments. It is one of the nASA's activities to study optimal decisions for uncertain systems and to make the result usable in economic, financial, ecological and resource planning. Over 40 participants from 12 different countries contributed to the success of the workshop, 12 papers were selected for this volume. Prof. A. Kurzhanskii Chairman of the Systems and Decision Sciences Program nASA Preface Optimization in an random environment has become an important branch of Applied Mathematics and Operations Research. It deals with optimal de­ cisions when only incomplete information of t.he future is available. Consider the following example: you have to make the decision about the amount of production although the future demand is unknown. If the size of the de­ mand can be described by a probability distribution, the problem is called a stochastic optimization problem.

• Discrete Event Systems
• Random Numbers
• Stochastic Optimization
• Stochastische Optimierung
• Zufallszahlen
• communication
• optimization
• simulation
• system

• Institut für Statistik und Informatik, Universität Wien, Wien, Austria

  Georg Pflug

• Institut für Statistik, Technische Universität Graz, Graz, Austria

  Ulrich Dieter

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